Lee Marcus
Aquatic Ecology, Department of Biology, Lund University, Lund, Sweden.
Department of Biology, University of Texas at Arlington, Arlington, USA.
Sci Rep. 2025 Jan 29;15(1):3626. doi: 10.1038/s41598-025-87334-8.
Environmental variation has long been considered a key driver of evolutionary change, predicted to shape different strategies, such as genetic specialization, plasticity, or bet-hedging to maintain fitness. However, little evidence is available with regards to how the periodicity of stressors may impact fitness across generations. To address this gap, I conducted a reciprocal split-brood experiment using the freshwater crustacean, Daphnia magna, and an ecologically relevant environmental stressor, ultraviolet radiation (UVR). I exposed one group to constant and another group to fluctuating UVR conditions. Despite receiving the same dose of UVR, the first experimental generation displayed significant treatment-by-genotype interactions with respect to survival and reproductive output, as well as a delayed reproductive maturity under fluctuating UVR conditions. In the following experimental generation individuals exposed to fluctuating UVR exhibited higher fitness than those in a constant UVR regime. The ancestral conditions, i.e., maternal environment, however affected the survival probability and reproductive output, but did not significantly influence the maturation date. Overall, I demonstrate that the delivery of a stressor, not just its intensity, can have profound fitness consequences across generations, with important implications for seasonal succession of genotype-phenotype patterns in natural environments.
长期以来，环境变异一直被认为是进化变化的关键驱动因素，预计它会塑造不同的策略，如基因特化、可塑性或风险对冲，以维持适应性。然而，关于应激源的周期性如何影响多代的适应性，目前几乎没有证据。为了填补这一空白，我使用淡水甲壳类动物大型溞和一种具有生态相关性的环境应激源紫外线辐射（UVR）进行了一项相互分窝实验。我将一组暴露于恒定的UVR条件下，另一组暴露于波动的UVR条件下。尽管接受了相同剂量的UVR，但第一代实验群体在生存和繁殖产出方面表现出显著的处理与基因型相互作用，并且在波动的UVR条件下生殖成熟延迟。在接下来的实验代中，暴露于波动UVR的个体比处于恒定UVR条件下的个体表现出更高的适应性。然而，祖先条件，即母体环境，影响了生存概率和繁殖产出，但对成熟日期没有显著影响。总体而言，我证明了应激源的传递，而不仅仅是其强度，会对多代适应性产生深远影响，这对自然环境中基因型-表型模式的季节性演替具有重要意义。
